How to convert a NumPy array to PIL image applying matplotlib colormap

  • input = numpy_image
  • np.unit8 -> converts to integers
  • convert('RGB') -> converts to RGB
  • Image.fromarray -> returns an image object

    from PIL import Image
    import numpy as np
    
    PIL_image = Image.fromarray(np.uint8(numpy_image)).convert('RGB')
    
    PIL_image = Image.fromarray(numpy_image.astype('uint8'), 'RGB')
    

The method described in the accepted answer didn't work for me even after applying changes mentioned in its comments. But the below simple code worked:

import matplotlib.pyplot as plt
plt.imsave(filename, np_array, cmap='Greys')

np_array could be either a 2D array with values from 0..1 floats o2 0..255 uint8, and in that case it needs cmap. For 3D arrays, cmap will be ignored.


Quite a busy one-liner, but here it is:

  1. First ensure your NumPy array, myarray, is normalised with the max value at 1.0.
  2. Apply the colormap directly to myarray.
  3. Rescale to the 0-255 range.
  4. Convert to integers, using np.uint8().
  5. Use Image.fromarray().

And you're done:

from PIL import Image
from matplotlib import cm
im = Image.fromarray(np.uint8(cm.gist_earth(myarray)*255))

with plt.savefig():

Enter image description here

with im.save():

Enter image description here